局部放电(partial discharge，PD)(简称局放)信号易受噪声干扰，影响监测效果。针对局放信号噪声抑制问题，提出了一种局放信号稀疏表示去噪方法。该方法以信号的稀疏表示及其匹配追踪算法为核心，构建了与局放信号特征相匹配而与噪声信号不相关的局放脉冲匹配原子，并组成过完备原子库。在该原子库中采用匹配追踪算法对染噪局放信号进行稀疏表示，提取最佳局放脉冲匹配原子；并通过改进量子遗传算法加速最佳匹配原子搜索进程，减小计算时间复杂度；同时以残差比阈值作为MP算法迭代终止条件，避免因迭代次数选取不当对去噪结果的影响。最后利用各次迭代提取的最佳脉冲匹配原子仅能对染噪局放信号中原始无噪局放分量进行有效稀疏表示实现去噪目的。运用该方法对仿真信号及实测信号进行了去噪处理，并与基于传统小波理论的局放去噪结果作对比。结果表明，该方法能准确抑制局放信号的噪声干扰，去噪效果优于传统小波方法。“,”Partial discharge (PD) signal is susceptible to noise interference, which will bring influence to monitoring effect. Focusing on the noise suppression, a PD signal denoising method based on sparse representation was given in this paper. The core of this method is signal sparse representation and its matching pursuit(MP) algorithm. The PD pulse matching atom that matching the features of PD pulse signal while mismatching noise signal was designed, and the overcomplete dictionary was built as well. Based upon these, polluted PD signal was sparse decomposed by MP algorithm in this dictionary to search the best PD pulse matching atom. To decrease the calculation time complexity, the searching process of best PD pulse matching atoms were accelerated by improving quantum genetic algorithm (IQGA); morever, to avoid the influence on the denoising result by inappropriate choice of iterations, the residual ratio was chosen to be the terminating condition of the iteration. Finally only the original PD signal could be sparse represented by the best PD pulse matching atoms extracted during iteration and then the goal of denoising was achieved. The denoising method presented in this article was applied on the simulated and fielding measuring signals, the result was critical compared with denoising method based on wavelet as well. The results show that the denoising method of this paper is available to precisely suppress PD signal noise jamming and the denoising effect is superior to the traditional wavelet method.